In the world of military and defense-related operations, assets may operate at many levels. Among these, tactical or front-line assets that go into harm's way directly interface with targets and threats. At the top level are the strategic decision makers, who do not go into harm's way, but require as much accurate and timely information as can be obtained in order plan a path to mission success. In between these are mid-level assets structured in the chain of command to most efficiently link the front-line assets with the strategic decision makers. Due to the different objectives and reaction times required, front-line and mid-level assets necessarily have customized levels of autonomy, and therefore must be able to make timely decisions at their level.
Front-line (tactical) assets (e.g., tanks, planes, ships, helicopters) must be able to cooperatively sense and engage targets and threats. Front-line assets must be able to cooperatively complete the Detect-Analyze-Respond cycle using terse, narrowly-defined tactical data sets in real-time time spans of milliseconds-to-seconds in order to achieve their missions and survive. Therefore, tactical information systems must be fast and accurate enough to put metal on target in time, which drives a terseness of volume and detail in the data handled.
Mid-level (operational) assets (ships, planes, command and intelligence centers) must be able to receive tactical and intelligence information from assets across multiple areas of responsibility, and to correlate information, see growing trends and make decisions across this bigger picture. Mid-level and front-line assets must cooperatively complete a Detect-Analyze-Respond cycle, using this larger and richer set of data, in near-real-time time spans of seconds-to-hours in order to achieve mid-level missions. Therefore, supporting information systems must be able to balance performance with the ability to handle a much larger and richer set of data than the tactical information systems.
Top-level (strategic) assets (command and intelligence centers) must be able to receive tactical and intelligence information from assets across all their areas of responsibility, and to correlate information, see long-term trends and make decisions that require the broadest level of information integration possible. Top-level, mid-level and front-line assets must cooperatively complete a Detect-Analyze-Respond cycle, with this huge data set, in non-real-time time spans of hours-to-days in order to achieve top-level or strategic missions. Therefore, supporting information systems must be able to handle huge volumes of data with rich and varied detail.
Although fast and effective tactical information systems have existed for many years, today's mid and top-level information management is not done reliably or consistently. In the existing military environment, information at this level is handled by a patchwork of tactical and intelligence systems that have each grown organically from the niche in which they were conceived. There is no native interoperability or common data model between these systems: they can only share information through customized interfaces that result in overall performance degradation and loss of detail in the total data set. Furthermore, there is no military information system today capable of handling the huge and richly detailed top-level data set in a way that supports today's best automated data analysis and management techniques. Instead, this work is often still done with paper and pencil, depending on the experience, intuition and ingenuity of the commanders and analysts to successfully navigate the sea of information without drowning.
Improved information management systems are desired to provide the information management (decision support) capability required at these higher levels.